CLUTO is a software package for clustering low- and high-dimensional datasets and for analyzing the characteristics of the various clusters. CLUTO is well-suited for clustering data sets arising in many diverse application areas including information retrieval, customer purchasing transactions, web, GIS, science, and biology. CLUTO provides three different classes of clustering algorithms that operate either directly in the object's feature space or in the object's similarity space. These algorithms are based on the partitional, agglomerative, and graph-partitioning paradigms. A key feature in most of CLUTO's clustering algorithms is that they treat the clustering problem as an optimization process which seeks to maximize or minimize a particular clustering criterion function defined either globally or locally over the entire clustering solution space. CLUTO provides a total of seven different criterion functions that can be used to drive both partitional and agglomerative clustering algorithms, that are described and analyzed in [ZK01, ZK02b]. Most of these criterion functions have been shown to produce high quality clustering solutions in high dimensional datasets, especially those arising in document clustering. In addition, CLUTO provides some of the more traditional local criteria (e.g., single-link, complete-link, and UPGMA) that can be used in the context of agglomerative clustering. Furthermore, CLUTO provides graph-partitioning-based clustering algorithms that are well-suited for finding clusters that form contiguous regions that span different dimensions of the underlying feature space CLUTO also provides tools for analyzing the discovered clusters to understand the relations between the objects assigned to each cluster and the relations between the different clusters. In particular, CLUTO can identify the features that best describe and/or discriminate each cluster. These set of features can be used to gain a better understanding of the set of objects assigned to each cluster and to provide concise summaries about the cluster's contents. Moreover, CLUTO provides visualization tools that can be used to see the relationships between the clusters, objects, and features. CLUTO's distribution consists of both stand-alone programs and a library via which an application program can access directly the various clustering and analysis algorithms implemented in CLUTO. |
